You are the forecaster responsible for hurricane warnings on the southeast corner of the United States in September. Anyone that has lived in North Carolina for a while knows what is it is like at that time of the year, for example. The cost of issuing a warning like a hurricane involves people taking shelter, business stopping, the areas's economy paused - a moderate cost of C dollars. You also know the preventable loss should a hurricane come and the area be unprepared: property damage, lives lost -an extremely high loss of L dollars. Your weather forecast indicates hurricane with a probability of p. (a) Should you issue a warning? Use expectations to create a decision rule for whether issuing or not a warning. Explain your rule.
(b) For what kind of extreme weather warnings is the decision more likely to be "do not warn" than "warn"? Explain.

A)

C ≤ LP   issue warning

C > LP do not issue warning

B )

For ' do not warm ' the condition will be that C is moderate while L is extremely high

Step-by-step explanation:

Assuming Y is an indicator that represents if a warning is issued or not

probability of occurrence of Hurricane = p

where;  C = cost of issuing a warning

             L = cost incurred for not issuing warning

A) Determine if you should issue a warning or not

In this scenario there are about four possible cases

hence the expected cost ( E ) = L ( 1 - Y )p  + Cy

when warning is issued = Y ( 1 )

expected cost ( E ) = C

assuming warning is not issued then Y = 0

hence expected cost ( E ) = LP

Hence the decision rule will be :

C ≤ LP   issue warning

C > LP do not issue warning

B) For ' do not warm ' the condition will be that C is moderate while L is extremely high ( as seen in the question ) because this will make  C/L to be very small. from the condition C > LP  and this simply means that the probability of the Hurricane occurring is very small

a. X is the number of DVDs a customer rents.

Step-by-step explanation:

The distribution states that:

0.05 = 5% probability a customer rents no DVDs

0.49 = 49% probability a customer rents 1 DVD

...

0.03 = 3% probability a customer rents 5 DVDs.

Thus, the random variable X is the number of DVDs a customer rents, and the correct answer is given by option A.